학술논문
Determination of ovarian transposition through prediction of postoperative adjuvant therapy in young patients with early stage cervical cancer undergoing surgery: a Korean multicenter retrospective study (KGOG 1042)
Document Type
Article
Author
Source
(2024): 296-303.
Subject
Language
Korean
Abstract
Objective We aimed to predict the risk of postoperative adjuvant therapy using preoperative variables in young patients with early stage cervical cancer. The predicted risk can guide whether ovarian transposition should be performed during surgery. Methods In total, 886 patients with stage IB1-IIA cervical cancer aged 20-45 years who underwent modified radical or radical hysterectomy between January 2000 and December 2008 were included. Preoperative variables, preoperative laboratory findings, International Federation of Gynaecology and Obstetrics stage, tumor size, and pathological variables were collected. Patients with high risk factors or those who met the Sedlis criteria were considered adjuvant therapy risk (+); others were considered adjuvant therapy risk (-). A decision-tree model using preoperative variables was constructed to predict the risk of adjuvant therapy. Results Of 886 patients, 362 were adjuvant therapy risk (+) (40.9%). The decision-tree model with four distinct adjuvant therapy risks using tumor size and age were generated. Specifically, patients with tumor size ≤2.45 cm had low risk (49/367; 13.4%), those with tumor size ≤3.85 cm and >2.45 cm had moderate risk (136/314; 43.3%), those with tumor size >3.85 cm and age ≤39.5 years had high risk (92/109; 84.4%), and those with tumor size >3.85 cm and age >39.5 years had the highest risk (85/96; 88.5%). Conclusion The risk of postoperative adjuvant therapy in young patients with early stage cervical cancer can be predicted using preoperative variables. We can decide whether ovarian transposition should be performed using the predicted risk.
Objective We aimed to predict the risk of postoperative adjuvant therapy using preoperative variables in young patients with early stage cervical cancer. The predicted risk can guide whether ovarian transposition should be performed during surgery. Methods In total, 886 patients with stage IB1-IIA cervical cancer aged 20-45 years who underwent modified radical or radical hysterectomy between January 2000 and December 2008 were included. Preoperative variables, preoperative laboratory findings, International Federation of Gynaecology and Obstetrics stage, tumor size, and pathological variables were collected. Patients with high risk factors or those who met the Sedlis criteria were considered adjuvant therapy risk (+); others were considered adjuvant therapy risk (-). A decision-tree model using preoperative variables was constructed to predict the risk of adjuvant therapy. Results Of 886 patients, 362 were adjuvant therapy risk (+) (40.9%). The decision-tree model with four distinct adjuvant therapy risks using tumor size and age were generated. Specifically, patients with tumor size ≤2.45 cm had low risk (49/367; 13.4%), those with tumor size ≤3.85 cm and >2.45 cm had moderate risk (136/314; 43.3%), those with tumor size >3.85 cm and age ≤39.5 years had high risk (92/109; 84.4%), and those with tumor size >3.85 cm and age >39.5 years had the highest risk (85/96; 88.5%). Conclusion The risk of postoperative adjuvant therapy in young patients with early stage cervical cancer can be predicted using preoperative variables. We can decide whether ovarian transposition should be performed using the predicted risk.
Objective We aimed to predict the risk of postoperative adjuvant therapy using preoperative variables in young patients with early stage cervical cancer. The predicted risk can guide whether ovarian transposition should be performed during surgery. Methods In total, 886 patients with stage IB1-IIA cervical cancer aged 20-45 years who underwent modified radical or radical hysterectomy between January 2000 and December 2008 were included. Preoperative variables, preoperative laboratory findings, International Federation of Gynaecology and Obstetrics stage, tumor size, and pathological variables were collected. Patients with high risk factors or those who met the Sedlis criteria were considered adjuvant therapy risk (+); others were considered adjuvant therapy risk (-). A decision-tree model using preoperative variables was constructed to predict the risk of adjuvant therapy. Results Of 886 patients, 362 were adjuvant therapy risk (+) (40.9%). The decision-tree model with four distinct adjuvant therapy risks using tumor size and age were generated. Specifically, patients with tumor size ≤2.45 cm had low risk (49/367; 13.4%), those with tumor size ≤3.85 cm and >2.45 cm had moderate risk (136/314; 43.3%), those with tumor size >3.85 cm and age ≤39.5 years had high risk (92/109; 84.4%), and those with tumor size >3.85 cm and age >39.5 years had the highest risk (85/96; 88.5%). Conclusion The risk of postoperative adjuvant therapy in young patients with early stage cervical cancer can be predicted using preoperative variables. We can decide whether ovarian transposition should be performed using the predicted risk.